The transportation network is straining to keep up with the increased traffic as a result of the mixed traffic system and unregulated growth of private modes. Over-speeding and congestion are the two main issues for urban planners. Speed management measures and effective enforcement are necessary to reduce over-speeding, which is the major cause of traffic accidents. Hence this study works in finding an efficient measure to achieve traffic speed management and thus examines how well Automatic Number Plate Recognition (ANPR) and The Infra-Red Traffic Logger (TIRTL) systems function in terms of collecting traffic data and identifying over-speeding vehicles. Results revealed that the ANPR correctly detected only 51% of the total vehicle classes, whereas TIRTL correctly detected 96% of the vehicle classes. A maximum speed reduction of 20 km/h has been observed in the car, with an average speed reduction of 8 km/h. Finally, the developed ANN model might aid urban planners in creating new speed management technique efforts by properly estimating the correctness of the speed management technique in an urban setting.